A particle swarm optimization levy flight algorithm for imputation of missing creatinine dataset

Ismail, Amelia Ritahani and Abdul Aziz, Normaziah and Md Ralib, Azrina and Zainal Abidin, Nadzurah and Basath, Samar Salem (2021) A particle swarm optimization levy flight algorithm for imputation of missing creatinine dataset. International Journal of Advances in Intelligent Informatics, 7 (2). pp. 225-236. ISSN 2442-6571 E-ISSN 2648-3161

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Abstract

Clinicians could intervene during what may be a crucial stage for preventing permanent kidney injury if patients with incipient Acute Kidney Injury (AKI) and those at high risk of developing AKI could be identified. This paper proposes an improved mechanism to machine learning imputation algorithms by introducing the Particle Swarm Levy Flight algorithm. We improve the algorithms by modifying the Particle Swarm Optimization Algorithm (PSO), by enhancing the algorithm with levy flight (PSOLF). The creatinine dataset that we collected, including AKI diagnosis and staging, mortality at hospital discharge, and renal recovery, are tested and compared with other machine learning algorithms such as Genetic Algorithm and traditional PSO. The proposed algorithms' performances are validated with a statistical significance test. The results show that SVMPSOLF has better performance than the other method. This research could be useful as an important tool of prognostic capabilities for determining which patients are likely to suffer from AKI, potentially allowing clinicians to intervene before kidney damage manifests.

Item Type:	Article (Journal)
Uncontrolled Keywords:	Baseline creatinine Imputation, Missing data Particle swarm optimization, Levy flight
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button):	Kulliyyah of Information and Communication Technology Kulliyyah of Information and Communication Technology Kulliyyah of Information and Communication Technology > Department of Computer Science Kulliyyah of Information and Communication Technology > Department of Computer Science
Depositing User:	Amelia Ritahani Ismail
Date Deposited:	19 Nov 2021 21:00
Last Modified:	20 Dec 2021 14:54
URI:	http://irep.iium.edu.my/id/eprint/93912

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